Overview

Dataset statistics

Number of variables18
Number of observations377185
Missing cells1869153
Missing cells (%)27.5%
Duplicate rows49
Duplicate rows (%)< 0.1%
Total size in memory51.8 MiB
Average record size in memory144.0 B

Variable types

Text15
Boolean2
Categorical1

Alerts

private pool has constant value "True"Constant
PrivatePool has constant value "True"Constant
Dataset has 49 (< 0.1%) duplicate rowsDuplicates
status has 39918 (10.6%) missing valuesMissing
private pool has 373004 (98.9%) missing valuesMissing
propertyType has 34733 (9.2%) missing valuesMissing
baths has 106338 (28.2%) missing valuesMissing
fireplace has 274071 (72.7%) missing valuesMissing
sqft has 40577 (10.8%) missing valuesMissing
beds has 91282 (24.2%) missing valuesMissing
stories has 150716 (40.0%) missing valuesMissing
mls-id has 352243 (93.4%) missing valuesMissing
PrivatePool has 336874 (89.3%) missing valuesMissing
MlsId has 66880 (17.7%) missing valuesMissing

Reproduction

Analysis started2024-05-28 12:12:17.542458
Analysis finished2024-05-28 12:14:32.856507
Duration2 minutes and 15.31 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

status
Text

MISSING 

Distinct159
Distinct (%)< 0.1%
Missing39918
Missing (%)10.6%
Memory size2.9 MiB
2024-05-28T12:14:33.118937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length38
Median length8
Mean length7.8409183
Min length1

Characters and Unicode

Total characters2644483
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)< 0.1%

Sample

1st rowActive
2nd rowfor sale
3rd rowfor sale
4th rowfor sale
5th rowfor sale
ValueCountFrequency (%)
for 199983
35.8%
sale 199634
35.8%
active 106540
19.1%
foreclosure 6771
 
1.2%
new 6165
 
1.1%
construction 5475
 
1.0%
pending 5364
 
1.0%
contract 3802
 
0.7%
pre-foreclosure 3679
 
0.7%
under 3661
 
0.7%
Other values (125) 17013
 
3.0%
2024-05-28T12:14:33.809467image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 351490
13.3%
o 244796
9.3%
r 239503
9.1%
223406
8.4%
s 217112
8.2%
l 211183
8.0%
a 207546
7.8%
f 166776
 
6.3%
c 137402
 
5.2%
t 132032
 
5.0%
Other values (52) 513237
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2644483
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 351490
13.3%
o 244796
9.3%
r 239503
9.1%
223406
8.4%
s 217112
8.2%
l 211183
8.0%
a 207546
7.8%
f 166776
 
6.3%
c 137402
 
5.2%
t 132032
 
5.0%
Other values (52) 513237
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2644483
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 351490
13.3%
o 244796
9.3%
r 239503
9.1%
223406
8.4%
s 217112
8.2%
l 211183
8.0%
a 207546
7.8%
f 166776
 
6.3%
c 137402
 
5.2%
t 132032
 
5.0%
Other values (52) 513237
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2644483
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 351490
13.3%
o 244796
9.3%
r 239503
9.1%
223406
8.4%
s 217112
8.2%
l 211183
8.0%
a 207546
7.8%
f 166776
 
6.3%
c 137402
 
5.2%
t 132032
 
5.0%
Other values (52) 513237
19.4%

private pool
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing373004
Missing (%)98.9%
Memory size736.8 KiB
True
 
4181
(Missing)
373004 
ValueCountFrequency (%)
True 4181
 
1.1%
(Missing) 373004
98.9%
2024-05-28T12:14:34.121096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

propertyType
Text

MISSING 

Distinct1280
Distinct (%)0.4%
Missing34733
Missing (%)9.2%
Memory size2.9 MiB
2024-05-28T12:14:34.610043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length129
Median length112
Mean length13.522067
Min length1

Characters and Unicode

Total characters4630659
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique615 ?
Unique (%)0.2%

Sample

1st rowSingle Family Home
2nd rowsingle-family home
3rd rowsingle-family home
4th rowsingle-family home
5th rowlot/land
ValueCountFrequency (%)
home 126898
21.0%
single 98013
16.2%
family 97391
16.1%
single-family 92206
15.2%
condo 42532
 
7.0%
lot/land 20552
 
3.4%
townhouse 18579
 
3.1%
land 10939
 
1.8%
traditional 9679
 
1.6%
multi-family 9424
 
1.6%
Other values (277) 79448
13.1%
2024-05-28T12:14:35.788702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 465212
 
10.0%
i 441168
 
9.5%
e 398458
 
8.6%
o 376556
 
8.1%
m 361450
 
7.8%
n 336503
 
7.3%
a 283147
 
6.1%
263457
 
5.7%
y 210598
 
4.5%
g 193479
 
4.2%
Other values (58) 1300631
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4630659
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 465212
 
10.0%
i 441168
 
9.5%
e 398458
 
8.6%
o 376556
 
8.1%
m 361450
 
7.8%
n 336503
 
7.3%
a 283147
 
6.1%
263457
 
5.7%
y 210598
 
4.5%
g 193479
 
4.2%
Other values (58) 1300631
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4630659
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 465212
 
10.0%
i 441168
 
9.5%
e 398458
 
8.6%
o 376556
 
8.1%
m 361450
 
7.8%
n 336503
 
7.3%
a 283147
 
6.1%
263457
 
5.7%
y 210598
 
4.5%
g 193479
 
4.2%
Other values (58) 1300631
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4630659
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 465212
 
10.0%
i 441168
 
9.5%
e 398458
 
8.6%
o 376556
 
8.1%
m 361450
 
7.8%
n 336503
 
7.3%
a 283147
 
6.1%
263457
 
5.7%
y 210598
 
4.5%
g 193479
 
4.2%
Other values (58) 1300631
28.1%

street
Text

Distinct337076
Distinct (%)89.4%
Missing2
Missing (%)< 0.1%
Memory size2.9 MiB
2024-05-28T12:14:36.648645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length96
Median length83
Mean length18.581755
Min length1

Characters and Unicode

Total characters7008722
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302913 ?
Unique (%)80.3%

Sample

1st row240 Heather Ln
2nd row12911 E Heroy Ave
3rd row2005 Westridge Rd
4th row4311 Livingston Ave
5th row1524 Kiscoe St
ValueCountFrequency (%)
st 83457
 
5.7%
dr 64519
 
4.4%
ave 62480
 
4.2%
rd 32631
 
2.2%
ln 23003
 
1.6%
n 18922
 
1.3%
w 18434
 
1.3%
ct 17819
 
1.2%
s 17722
 
1.2%
sw 15625
 
1.1%
Other values (69379) 1116671
75.9%
2024-05-28T12:14:38.015959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1155250
 
16.5%
e 358127
 
5.1%
1 338548
 
4.8%
r 287515
 
4.1%
t 285628
 
4.1%
a 269227
 
3.8%
n 248642
 
3.5%
0 232055
 
3.3%
2 222173
 
3.2%
l 209098
 
3.0%
Other values (77) 3402459
48.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7008722
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1155250
 
16.5%
e 358127
 
5.1%
1 338548
 
4.8%
r 287515
 
4.1%
t 285628
 
4.1%
a 269227
 
3.8%
n 248642
 
3.5%
0 232055
 
3.3%
2 222173
 
3.2%
l 209098
 
3.0%
Other values (77) 3402459
48.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7008722
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1155250
 
16.5%
e 358127
 
5.1%
1 338548
 
4.8%
r 287515
 
4.1%
t 285628
 
4.1%
a 269227
 
3.8%
n 248642
 
3.5%
0 232055
 
3.3%
2 222173
 
3.2%
l 209098
 
3.0%
Other values (77) 3402459
48.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7008722
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1155250
 
16.5%
e 358127
 
5.1%
1 338548
 
4.8%
r 287515
 
4.1%
t 285628
 
4.1%
a 269227
 
3.8%
n 248642
 
3.5%
0 232055
 
3.3%
2 222173
 
3.2%
l 209098
 
3.0%
Other values (77) 3402459
48.5%

baths
Text

MISSING 

Distinct229
Distinct (%)0.1%
Missing106338
Missing (%)28.2%
Memory size2.9 MiB
2024-05-28T12:14:38.571961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length19
Mean length5.4117048
Min length1

Characters and Unicode

Total characters1465744
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)< 0.1%

Sample

1st row3.5
2nd row3 Baths
3rd row2 Baths
4th row8 Baths
5th row2
ValueCountFrequency (%)
baths 121289
28.7%
2 85147
20.2%
3 54127
12.8%
bathrooms 23281
 
5.5%
4 21450
 
5.1%
2.0 16576
 
3.9%
2.5 12892
 
3.1%
3.0 10869
 
2.6%
1 10579
 
2.5%
5 7666
 
1.8%
Other values (128) 58522
13.9%
2024-05-28T12:14:39.620696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151753
10.4%
a 151195
10.3%
t 144772
9.9%
s 144570
9.9%
h 144570
9.9%
B 144054
9.8%
2 122744
8.4%
0 74485
 
5.1%
3 72973
 
5.0%
. 64765
 
4.4%
Other values (25) 249863
17.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1465744
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
151753
10.4%
a 151195
10.3%
t 144772
9.9%
s 144570
9.9%
h 144570
9.9%
B 144054
9.8%
2 122744
8.4%
0 74485
 
5.1%
3 72973
 
5.0%
. 64765
 
4.4%
Other values (25) 249863
17.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1465744
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
151753
10.4%
a 151195
10.3%
t 144772
9.9%
s 144570
9.9%
h 144570
9.9%
B 144054
9.8%
2 122744
8.4%
0 74485
 
5.1%
3 72973
 
5.0%
. 64765
 
4.4%
Other values (25) 249863
17.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1465744
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
151753
10.4%
a 151195
10.3%
t 144772
9.9%
s 144570
9.9%
h 144570
9.9%
B 144054
9.8%
2 122744
8.4%
0 74485
 
5.1%
3 72973
 
5.0%
. 64765
 
4.4%
Other values (25) 249863
17.0%
Distinct321009
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2024-05-28T12:14:40.751826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length840
Median length605
Mean length374.50896
Min length334

Characters and Unicode

Total characters141259163
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique311038 ?
Unique (%)82.5%

Sample

1st row{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Central A/C, Heat Pump', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$144', 'factLabel': 'Price/sqft'}]}
2nd row{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '5828 sqft', 'factLabel': 'lotsize'}, {'factValue': '$159/sqft', 'factLabel': 'Price/sqft'}]}
3rd row{'atAGlanceFacts': [{'factValue': '1961', 'factLabel': 'Year built'}, {'factValue': '1967', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '8,626 sqft', 'factLabel': 'lotsize'}, {'factValue': '$965/sqft', 'factLabel': 'Price/sqft'}]}
4th row{'atAGlanceFacts': [{'factValue': '2006', 'factLabel': 'Year built'}, {'factValue': '2006', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Detached Garage', 'factLabel': 'Parking'}, {'factValue': '8,220 sqft', 'factLabel': 'lotsize'}, {'factValue': '$371/sqft', 'factLabel': 'Price/sqft'}]}
5th row{'atAGlanceFacts': [{'factValue': '', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '10,019 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}
ValueCountFrequency (%)
factlabel 2640295
20.7%
factvalue 2640295
20.7%
757424
 
5.9%
year 754370
 
5.9%
cooling 390962
 
3.1%
heating 389267
 
3.1%
parking 383675
 
3.0%
price/sqft 377185
 
3.0%
lotsize 377185
 
3.0%
ataglancefacts 377185
 
3.0%
Other values (29472) 3668656
28.8%
2024-05-28T12:14:42.135965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 21620955
15.3%
a 14183171
 
10.0%
12379318
 
8.8%
e 9771911
 
6.9%
t 8594876
 
6.1%
l 7533640
 
5.3%
c 6890716
 
4.9%
f 5960366
 
4.2%
: 5657791
 
4.0%
, 5126864
 
3.6%
Other values (76) 43539555
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 141259163
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 21620955
15.3%
a 14183171
 
10.0%
12379318
 
8.8%
e 9771911
 
6.9%
t 8594876
 
6.1%
l 7533640
 
5.3%
c 6890716
 
4.9%
f 5960366
 
4.2%
: 5657791
 
4.0%
, 5126864
 
3.6%
Other values (76) 43539555
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 141259163
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 21620955
15.3%
a 14183171
 
10.0%
12379318
 
8.8%
e 9771911
 
6.9%
t 8594876
 
6.1%
l 7533640
 
5.3%
c 6890716
 
4.9%
f 5960366
 
4.2%
: 5657791
 
4.0%
, 5126864
 
3.6%
Other values (76) 43539555
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 141259163
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 21620955
15.3%
a 14183171
 
10.0%
12379318
 
8.8%
e 9771911
 
6.9%
t 8594876
 
6.1%
l 7533640
 
5.3%
c 6890716
 
4.9%
f 5960366
 
4.2%
: 5657791
 
4.0%
, 5126864
 
3.6%
Other values (76) 43539555
30.8%

fireplace
Text

MISSING 

Distinct1652
Distinct (%)1.6%
Missing274071
Missing (%)72.7%
Memory size2.9 MiB
2024-05-28T12:14:42.757024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length231
Median length3
Mean length5.0304614
Min length1

Characters and Unicode

Total characters518711
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1038 ?
Unique (%)1.0%

Sample

1st rowGas Logs
2nd rowyes
3rd rowyes
4th rowyes
5th rowYes
ValueCountFrequency (%)
yes 71212
53.6%
1 15304
 
11.5%
room 3325
 
2.5%
fireplace 3304
 
2.5%
gas 3127
 
2.4%
2 2535
 
1.9%
not 1993
 
1.5%
applicable 1993
 
1.5%
closets 1725
 
1.3%
wood 1710
 
1.3%
Other values (350) 26724
 
20.1%
2024-05-28T12:14:43.900934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 93119
18.0%
s 81955
15.8%
y 52257
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15315
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 518711
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 93119
18.0%
s 81955
15.8%
y 52257
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15315
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 518711
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 93119
18.0%
s 81955
15.8%
y 52257
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15315
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 518711
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 93119
18.0%
s 81955
15.8%
y 52257
 
10.1%
29838
 
5.8%
Y 21802
 
4.2%
o 21186
 
4.1%
i 18735
 
3.6%
a 18442
 
3.6%
1 15315
 
3.0%
l 15193
 
2.9%
Other values (59) 150869
29.1%

city
Text

Distinct2026
Distinct (%)0.5%
Missing34
Missing (%)< 0.1%
Memory size2.9 MiB
2024-05-28T12:14:45.237247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length38
Median length29
Mean length8.9985735
Min length1

Characters and Unicode

Total characters3393821
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)0.1%

Sample

1st rowSouthern Pines
2nd rowSpokane Valley
3rd rowLos Angeles
4th rowDallas
5th rowPalm Bay
ValueCountFrequency (%)
houston 24460
 
4.8%
miami 20776
 
4.1%
san 19402
 
3.8%
antonio 15592
 
3.1%
fort 11470
 
2.3%
jacksonville 10375
 
2.1%
charlotte 9694
 
1.9%
dallas 8858
 
1.8%
beach 8785
 
1.7%
brooklyn 7298
 
1.4%
Other values (1701) 367717
72.9%
2024-05-28T12:14:48.337611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 343158
 
10.1%
o 283839
 
8.4%
n 257160
 
7.6%
e 248081
 
7.3%
l 224356
 
6.6%
i 219089
 
6.5%
t 194518
 
5.7%
s 159791
 
4.7%
r 151339
 
4.5%
127326
 
3.8%
Other values (50) 1185164
34.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3393821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 343158
 
10.1%
o 283839
 
8.4%
n 257160
 
7.6%
e 248081
 
7.3%
l 224356
 
6.6%
i 219089
 
6.5%
t 194518
 
5.7%
s 159791
 
4.7%
r 151339
 
4.5%
127326
 
3.8%
Other values (50) 1185164
34.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3393821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 343158
 
10.1%
o 283839
 
8.4%
n 257160
 
7.6%
e 248081
 
7.3%
l 224356
 
6.6%
i 219089
 
6.5%
t 194518
 
5.7%
s 159791
 
4.7%
r 151339
 
4.5%
127326
 
3.8%
Other values (50) 1185164
34.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3393821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 343158
 
10.1%
o 283839
 
8.4%
n 257160
 
7.6%
e 248081
 
7.3%
l 224356
 
6.6%
i 219089
 
6.5%
t 194518
 
5.7%
s 159791
 
4.7%
r 151339
 
4.5%
127326
 
3.8%
Other values (50) 1185164
34.9%
Distinct297365
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2024-05-28T12:14:49.234245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3688
Median length3289
Mean length301.95763
Min length68

Characters and Unicode

Total characters113893888
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265895 ?
Unique (%)70.5%

Sample

1st row[{'rating': ['4', '4', '7', 'NR', '4', '7', 'NR', 'NR'], 'data': {'Distance': ['2.7 mi', '3.6 mi', '5.1 mi', '4.0 mi', '10.5 mi', '12.6 mi', '2.7 mi', '3.1 mi'], 'Grades': ['3–5', '6–8', '9–12', 'PK–2', '6–8', '9–12', 'PK–5', 'K–12']}, 'name': ['Southern Pines Elementary School', 'Southern Middle School', 'Pinecrest High School', 'Southern Pines Primary School', "Crain's Creek Middle School", 'Union Pines High School', 'Episcopal Day Private School', 'Calvary Christian Private School']}]
2nd row[{'rating': ['4/10', 'None/10', '4/10'], 'data': {'Distance': ['1.65mi', '1.32mi', '1.01mi'], 'Grades': ['9-12', '3-8', 'PK-8']}, 'name': ['East Valley High School&Extension', 'Eastvalley Middle School', 'Trentwood Elementary School']}]
3rd row[{'rating': ['8/10', '4/10', '8/10'], 'data': {'Distance': ['1.19mi', '2.06mi', '2.63mi'], 'Grades': ['6-8', 'K-5', '9-12']}, 'name': ['Paul Revere Middle School', 'Brentwood Science School', 'Palisades Charter High School']}]
4th row[{'rating': ['9/10', '9/10', '10/10', '9/10'], 'data': {'Distance': ['1.05mi', '0.1mi', '1.05mi', '0.81mi'], 'Grades': ['5-6', 'PK-4', '7-8', '9-12']}, 'name': ['Mcculloch Intermediate School', 'Bradfield Elementary School', 'Highland Park Middle School', 'Highland Park High School']}]
5th row[{'rating': ['4/10', '5/10', '5/10'], 'data': {'Distance': ['5.96mi', '3.25mi', '3.03mi'], 'Grades': ['7-8', '9-12', 'PK-6']}, 'name': ['Southwest Middle School', 'Bayside High School', 'Westside Elementary School']}]
ValueCountFrequency (%)
school 1414258
 
9.8%
mi 906984
 
6.3%
elementary 446657
 
3.1%
high 438612
 
3.0%
name 377355
 
2.6%
grades 377288
 
2.6%
rating 377185
 
2.6%
data 377185
 
2.6%
distance 377185
 
2.6%
middle 322399
 
2.2%
Other values (16026) 9085018
62.7%
2024-05-28T12:14:51.600773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 16750056
 
14.7%
14127354
 
12.4%
, 6138741
 
5.4%
e 4777468
 
4.2%
o 4683179
 
4.1%
a 4603527
 
4.0%
i 4521043
 
4.0%
l 3313909
 
2.9%
t 3119253
 
2.7%
n 3061675
 
2.7%
Other values (74) 48797683
42.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 113893888
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 16750056
 
14.7%
14127354
 
12.4%
, 6138741
 
5.4%
e 4777468
 
4.2%
o 4683179
 
4.1%
a 4603527
 
4.0%
i 4521043
 
4.0%
l 3313909
 
2.9%
t 3119253
 
2.7%
n 3061675
 
2.7%
Other values (74) 48797683
42.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 113893888
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 16750056
 
14.7%
14127354
 
12.4%
, 6138741
 
5.4%
e 4777468
 
4.2%
o 4683179
 
4.1%
a 4603527
 
4.0%
i 4521043
 
4.0%
l 3313909
 
2.9%
t 3119253
 
2.7%
n 3061675
 
2.7%
Other values (74) 48797683
42.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 113893888
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 16750056
 
14.7%
14127354
 
12.4%
, 6138741
 
5.4%
e 4777468
 
4.2%
o 4683179
 
4.1%
a 4603527
 
4.0%
i 4521043
 
4.0%
l 3313909
 
2.9%
t 3119253
 
2.7%
n 3061675
 
2.7%
Other values (74) 48797683
42.8%

sqft
Text

MISSING 

Distinct25405
Distinct (%)7.5%
Missing40577
Missing (%)10.8%
Memory size2.9 MiB
2024-05-28T12:14:53.764839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length41
Median length40
Mean length9.3000196
Min length1

Characters and Unicode

Total characters3130461
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7325 ?
Unique (%)2.2%

Sample

1st row2900
2nd row1,947 sqft
3rd row3,000 sqft
4th row6,457 sqft
5th row897 sqft
ValueCountFrequency (%)
sqft 182737
29.8%
area 23678
 
3.9%
livable 23678
 
3.9%
interior 23678
 
3.9%
total 23678
 
3.9%
0 11854
 
1.9%
1,200 1298
 
0.2%
1,000 955
 
0.2%
1,500 911
 
0.1%
1,100 879
 
0.1%
Other values (14448) 320711
52.2%
2024-05-28T12:14:55.952492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
277449
 
8.9%
, 253135
 
8.1%
1 232504
 
7.4%
t 230093
 
7.4%
2 184940
 
5.9%
s 182737
 
5.8%
q 182737
 
5.8%
f 182737
 
5.8%
0 170258
 
5.4%
3 115328
 
3.7%
Other values (18) 1118543
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3130461
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
277449
 
8.9%
, 253135
 
8.1%
1 232504
 
7.4%
t 230093
 
7.4%
2 184940
 
5.9%
s 182737
 
5.8%
q 182737
 
5.8%
f 182737
 
5.8%
0 170258
 
5.4%
3 115328
 
3.7%
Other values (18) 1118543
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3130461
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
277449
 
8.9%
, 253135
 
8.1%
1 232504
 
7.4%
t 230093
 
7.4%
2 184940
 
5.9%
s 182737
 
5.8%
q 182737
 
5.8%
f 182737
 
5.8%
0 170258
 
5.4%
3 115328
 
3.7%
Other values (18) 1118543
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3130461
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
277449
 
8.9%
, 253135
 
8.1%
1 232504
 
7.4%
t 230093
 
7.4%
2 184940
 
5.9%
s 182737
 
5.8%
q 182737
 
5.8%
f 182737
 
5.8%
0 170258
 
5.4%
3 115328
 
3.7%
Other values (18) 1118543
35.7%
Distinct4549
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2024-05-28T12:14:57.224279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.9980593
Min length1

Characters and Unicode

Total characters1885193
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique598 ?
Unique (%)0.2%

Sample

1st row28387
2nd row99216
3rd row90049
4th row75205
5th row32908
ValueCountFrequency (%)
32137 2141
 
0.6%
33131 1563
 
0.4%
34747 1488
 
0.4%
78245 1390
 
0.4%
34759 1333
 
0.4%
33132 1328
 
0.4%
33137 1308
 
0.3%
78253 1282
 
0.3%
78254 1238
 
0.3%
33130 1170
 
0.3%
Other values (4539) 362944
96.2%
2024-05-28T12:14:58.506234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 336087
17.8%
1 233614
12.4%
2 233487
12.4%
7 230508
12.2%
0 221306
11.7%
4 151634
8.0%
8 148263
7.9%
9 120899
 
6.4%
6 105045
 
5.6%
5 104106
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1885193
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 336087
17.8%
1 233614
12.4%
2 233487
12.4%
7 230508
12.2%
0 221306
11.7%
4 151634
8.0%
8 148263
7.9%
9 120899
 
6.4%
6 105045
 
5.6%
5 104106
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1885193
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 336087
17.8%
1 233614
12.4%
2 233487
12.4%
7 230508
12.2%
0 221306
11.7%
4 151634
8.0%
8 148263
7.9%
9 120899
 
6.4%
6 105045
 
5.6%
5 104106
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1885193
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 336087
17.8%
1 233614
12.4%
2 233487
12.4%
7 230508
12.2%
0 221306
11.7%
4 151634
8.0%
8 148263
7.9%
9 120899
 
6.4%
6 105045
 
5.6%
5 104106
 
5.5%

beds
Text

MISSING 

Distinct1184
Distinct (%)0.4%
Missing91282
Missing (%)24.2%
Memory size2.9 MiB
2024-05-28T12:14:59.277815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length122
Median length121
Mean length4.1196
Min length1

Characters and Unicode

Total characters1177806
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique715 ?
Unique (%)0.3%

Sample

1st row4
2nd row3 Beds
3rd row3 Beds
4th row5 Beds
5th row2 Beds
ValueCountFrequency (%)
beds 133199
29.3%
3 97751
21.5%
4 63717
14.0%
2 47731
 
10.5%
bd 32127
 
7.1%
5 20337
 
4.5%
baths 15283
 
3.4%
3.0 8088
 
1.8%
6 6276
 
1.4%
1 5744
 
1.3%
Other values (1126) 23708
 
5.2%
2024-05-28T12:15:00.960680image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168960
14.3%
d 165341
14.0%
s 151538
12.9%
B 149236
12.7%
e 134898
11.5%
3 106736
9.1%
4 69967
5.9%
2 51383
 
4.4%
b 32131
 
2.7%
5 22785
 
1.9%
Other values (46) 124831
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1177806
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
168960
14.3%
d 165341
14.0%
s 151538
12.9%
B 149236
12.7%
e 134898
11.5%
3 106736
9.1%
4 69967
5.9%
2 51383
 
4.4%
b 32131
 
2.7%
5 22785
 
1.9%
Other values (46) 124831
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1177806
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
168960
14.3%
d 165341
14.0%
s 151538
12.9%
B 149236
12.7%
e 134898
11.5%
3 106736
9.1%
4 69967
5.9%
2 51383
 
4.4%
b 32131
 
2.7%
5 22785
 
1.9%
Other values (46) 124831
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1177806
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
168960
14.3%
d 165341
14.0%
s 151538
12.9%
B 149236
12.7%
e 134898
11.5%
3 106736
9.1%
4 69967
5.9%
2 51383
 
4.4%
b 32131
 
2.7%
5 22785
 
1.9%
Other values (46) 124831
10.6%

state
Categorical

Distinct39
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
FL
115449 
TX
83786 
NY
24479 
CA
23386 
NC
21862 
Other values (34)
108223 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters754370
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowNC
2nd rowWA
3rd rowCA
4th rowTX
5th rowFL

Common Values

ValueCountFrequency (%)
FL 115449
30.6%
TX 83786
22.2%
NY 24479
 
6.5%
CA 23386
 
6.2%
NC 21862
 
5.8%
TN 18340
 
4.9%
WA 13826
 
3.7%
OH 12588
 
3.3%
IL 8939
 
2.4%
NV 8482
 
2.2%
Other values (29) 46048
 
12.2%

Length

2024-05-28T12:15:01.698226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fl 115450
30.6%
tx 83786
22.2%
ny 24479
 
6.5%
ca 23386
 
6.2%
nc 21862
 
5.8%
tn 18340
 
4.9%
wa 13826
 
3.7%
oh 12588
 
3.3%
il 8939
 
2.4%
nv 8482
 
2.2%
Other values (28) 46047
 
12.2%

Most occurring characters

ValueCountFrequency (%)
L 124389
16.5%
F 115450
15.3%
T 104327
13.8%
X 83786
11.1%
N 76927
10.2%
C 56354
7.5%
A 55386
7.3%
Y 24569
 
3.3%
O 22698
 
3.0%
I 18122
 
2.4%
Other values (16) 72362
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 754370
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
L 124389
16.5%
F 115450
15.3%
T 104327
13.8%
X 83786
11.1%
N 76927
10.2%
C 56354
7.5%
A 55386
7.3%
Y 24569
 
3.3%
O 22698
 
3.0%
I 18122
 
2.4%
Other values (16) 72362
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 754370
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
L 124389
16.5%
F 115450
15.3%
T 104327
13.8%
X 83786
11.1%
N 76927
10.2%
C 56354
7.5%
A 55386
7.3%
Y 24569
 
3.3%
O 22698
 
3.0%
I 18122
 
2.4%
Other values (16) 72362
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 754370
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
L 124389
16.5%
F 115450
15.3%
T 104327
13.8%
X 83786
11.1%
N 76927
10.2%
C 56354
7.5%
A 55386
7.3%
Y 24569
 
3.3%
O 22698
 
3.0%
I 18122
 
2.4%
Other values (16) 72362
9.6%

stories
Text

MISSING 

Distinct347
Distinct (%)0.2%
Missing150716
Missing (%)40.0%
Memory size2.9 MiB
2024-05-28T12:15:02.601038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length42
Median length3
Mean length2.852439
Min length1

Characters and Unicode

Total characters645989
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)< 0.1%

Sample

1st row2.0
2nd row1.0
3rd row3.0
4th row2.0
5th rowOne
ValueCountFrequency (%)
1.0 67454
28.5%
2.0 55283
23.4%
1 24830
 
10.5%
2 20958
 
8.9%
3.0 11275
 
4.8%
0.0 7241
 
3.1%
one 6367
 
2.7%
3 5398
 
2.3%
story 4718
 
2.0%
0 4273
 
1.8%
Other values (266) 28640
12.1%
2024-05-28T12:15:03.646366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172813
26.8%
. 155919
24.1%
1 96437
14.9%
2 80167
12.4%
3 17634
 
2.7%
e 14174
 
2.2%
o 11316
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8164
 
1.3%
Other values (51) 70827
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 645989
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 172813
26.8%
. 155919
24.1%
1 96437
14.9%
2 80167
12.4%
3 17634
 
2.7%
e 14174
 
2.2%
o 11316
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8164
 
1.3%
Other values (51) 70827
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 645989
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 172813
26.8%
. 155919
24.1%
1 96437
14.9%
2 80167
12.4%
3 17634
 
2.7%
e 14174
 
2.2%
o 11316
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8164
 
1.3%
Other values (51) 70827
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 645989
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 172813
26.8%
. 155919
24.1%
1 96437
14.9%
2 80167
12.4%
3 17634
 
2.7%
e 14174
 
2.2%
o 11316
 
1.8%
9968
 
1.5%
r 8570
 
1.3%
t 8164
 
1.3%
Other values (51) 70827
11.0%

mls-id
Text

MISSING 

Distinct24907
Distinct (%)99.9%
Missing352243
Missing (%)93.4%
Memory size2.9 MiB
2024-05-28T12:15:04.092555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length12
Mean length7.8794002
Min length1

Characters and Unicode

Total characters196528
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24874 ?
Unique (%)99.7%

Sample

1st row19221142
2nd rowSR19195113
3rd row201909438
4th rowT3159863
5th rowT3204536
ValueCountFrequency (%)
no 8
 
< 0.1%
mls 5
 
< 0.1%
983469 2
 
< 0.1%
241766 2
 
< 0.1%
201906177 2
 
< 0.1%
74184012 2
 
< 0.1%
1020414 2
 
< 0.1%
19-5064 2
 
< 0.1%
201909981 2
 
< 0.1%
617190 2
 
< 0.1%
Other values (24897) 24922
99.9%
2024-05-28T12:15:04.959710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 31390
16.0%
0 22606
11.5%
2 21470
10.9%
9 18569
9.4%
4 17233
8.8%
5 15664
8.0%
6 14750
7.5%
3 14566
7.4%
7 14516
7.4%
8 14386
7.3%
Other values (47) 11378
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 196528
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 31390
16.0%
0 22606
11.5%
2 21470
10.9%
9 18569
9.4%
4 17233
8.8%
5 15664
8.0%
6 14750
7.5%
3 14566
7.4%
7 14516
7.4%
8 14386
7.3%
Other values (47) 11378
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 196528
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 31390
16.0%
0 22606
11.5%
2 21470
10.9%
9 18569
9.4%
4 17233
8.8%
5 15664
8.0%
6 14750
7.5%
3 14566
7.4%
7 14516
7.4%
8 14386
7.3%
Other values (47) 11378
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 196528
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 31390
16.0%
0 22606
11.5%
2 21470
10.9%
9 18569
9.4%
4 17233
8.8%
5 15664
8.0%
6 14750
7.5%
3 14566
7.4%
7 14516
7.4%
8 14386
7.3%
Other values (47) 11378
 
5.8%

PrivatePool
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing336874
Missing (%)89.3%
Memory size736.8 KiB
True
40311 
(Missing)
336874 
ValueCountFrequency (%)
True 40311
 
10.7%
(Missing) 336874
89.3%
2024-05-28T12:15:05.348953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

MlsId
Text

MISSING 

Distinct232944
Distinct (%)75.1%
Missing66880
Missing (%)17.7%
Memory size2.9 MiB
2024-05-28T12:15:06.388691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length60
Median length58
Mean length8.0889576
Min length1

Characters and Unicode

Total characters2510044
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171673 ?
Unique (%)55.3%

Sample

1st row611019
2nd row201916904
3rd rowFR19221027
4th row14191809
5th row861745
ValueCountFrequency (%)
fl 2265
 
0.7%
miami 884
 
0.3%
tx 772
 
0.2%
beach 351
 
0.1%
houston 332
 
0.1%
orlando 302
 
0.1%
lauderdale 246
 
0.1%
fort 241
 
0.1%
ca 213
 
0.1%
austin 206
 
0.1%
Other values (232028) 319295
98.2%
2024-05-28T12:15:08.633235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 359697
14.3%
0 275829
11.0%
2 243681
9.7%
4 222316
8.9%
5 215575
8.6%
3 197981
7.9%
9 194840
7.8%
7 194113
7.7%
6 193488
7.7%
8 187133
7.5%
Other values (66) 225391
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2510044
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 359697
14.3%
0 275829
11.0%
2 243681
9.7%
4 222316
8.9%
5 215575
8.6%
3 197981
7.9%
9 194840
7.8%
7 194113
7.7%
6 193488
7.7%
8 187133
7.5%
Other values (66) 225391
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2510044
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 359697
14.3%
0 275829
11.0%
2 243681
9.7%
4 222316
8.9%
5 215575
8.6%
3 197981
7.9%
9 194840
7.8%
7 194113
7.7%
6 193488
7.7%
8 187133
7.5%
Other values (66) 225391
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2510044
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 359697
14.3%
0 275829
11.0%
2 243681
9.7%
4 222316
8.9%
5 215575
8.6%
3 197981
7.9%
9 194840
7.8%
7 194113
7.7%
6 193488
7.7%
8 187133
7.5%
Other values (66) 225391
9.0%

target
Text

Distinct43939
Distinct (%)11.7%
Missing2481
Missing (%)0.7%
Memory size2.9 MiB
2024-05-28T12:15:10.166692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length18
Median length8
Mean length7.9461522
Min length1

Characters and Unicode

Total characters2977455
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29774 ?
Unique (%)7.9%

Sample

1st row$418,000
2nd row$310,000
3rd row$2,895,000
4th row$2,395,000
5th row$5,000
ValueCountFrequency (%)
225,000 1806
 
0.5%
275,000 1650
 
0.4%
250,000 1644
 
0.4%
350,000 1641
 
0.4%
325,000 1562
 
0.4%
399,000 1547
 
0.4%
299,900 1534
 
0.4%
249,900 1500
 
0.4%
299,000 1452
 
0.4%
375,000 1442
 
0.4%
Other values (34326) 358928
95.8%
2024-05-28T12:15:11.838373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 984828
33.1%
, 418551
14.1%
9 332567
 
11.2%
$ 308823
 
10.4%
5 183665
 
6.2%
2 147747
 
5.0%
1 138827
 
4.7%
4 121560
 
4.1%
3 110323
 
3.7%
7 77982
 
2.6%
Other values (8) 152582
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2977455
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 984828
33.1%
, 418551
14.1%
9 332567
 
11.2%
$ 308823
 
10.4%
5 183665
 
6.2%
2 147747
 
5.0%
1 138827
 
4.7%
4 121560
 
4.1%
3 110323
 
3.7%
7 77982
 
2.6%
Other values (8) 152582
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2977455
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 984828
33.1%
, 418551
14.1%
9 332567
 
11.2%
$ 308823
 
10.4%
5 183665
 
6.2%
2 147747
 
5.0%
1 138827
 
4.7%
4 121560
 
4.1%
3 110323
 
3.7%
7 77982
 
2.6%
Other values (8) 152582
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2977455
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 984828
33.1%
, 418551
14.1%
9 332567
 
11.2%
$ 308823
 
10.4%
5 183665
 
6.2%
2 147747
 
5.0%
1 138827
 
4.7%
4 121560
 
4.1%
3 110323
 
3.7%
7 77982
 
2.6%
Other values (8) 152582
 
5.1%

Missing values

2024-05-28T12:14:25.914744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-28T12:14:27.331931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-28T12:14:30.444581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

statusprivate poolpropertyTypestreetbathshomeFactsfireplacecityschoolssqftzipcodebedsstatestoriesmls-idPrivatePoolMlsIdtarget
0ActiveNaNSingle Family Home240 Heather Ln3.5{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Central A/C, Heat Pump', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$144', 'factLabel': 'Price/sqft'}]}Gas LogsSouthern Pines[{'rating': ['4', '4', '7', 'NR', '4', '7', 'NR', 'NR'], 'data': {'Distance': ['2.7 mi', '3.6 mi', '5.1 mi', '4.0 mi', '10.5 mi', '12.6 mi', '2.7 mi', '3.1 mi'], 'Grades': ['3–5', '6–8', '9–12', 'PK–2', '6–8', '9–12', 'PK–5', 'K–12']}, 'name': ['Southern Pines Elementary School', 'Southern Middle School', 'Pinecrest High School', 'Southern Pines Primary School', "Crain's Creek Middle School", 'Union Pines High School', 'Episcopal Day Private School', 'Calvary Christian Private School']}]2900283874NCNaNNaNNaN611019$418,000
1for saleNaNsingle-family home12911 E Heroy Ave3 Baths{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '5828 sqft', 'factLabel': 'lotsize'}, {'factValue': '$159/sqft', 'factLabel': 'Price/sqft'}]}NaNSpokane Valley[{'rating': ['4/10', 'None/10', '4/10'], 'data': {'Distance': ['1.65mi', '1.32mi', '1.01mi'], 'Grades': ['9-12', '3-8', 'PK-8']}, 'name': ['East Valley High School&Extension', 'Eastvalley Middle School', 'Trentwood Elementary School']}]1,947 sqft992163 BedsWA2.0NaNNaN201916904$310,000
2for saleNaNsingle-family home2005 Westridge Rd2 Baths{'atAGlanceFacts': [{'factValue': '1961', 'factLabel': 'Year built'}, {'factValue': '1967', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '8,626 sqft', 'factLabel': 'lotsize'}, {'factValue': '$965/sqft', 'factLabel': 'Price/sqft'}]}yesLos Angeles[{'rating': ['8/10', '4/10', '8/10'], 'data': {'Distance': ['1.19mi', '2.06mi', '2.63mi'], 'Grades': ['6-8', 'K-5', '9-12']}, 'name': ['Paul Revere Middle School', 'Brentwood Science School', 'Palisades Charter High School']}]3,000 sqft900493 BedsCA1.0NaNyesFR19221027$2,895,000
3for saleNaNsingle-family home4311 Livingston Ave8 Baths{'atAGlanceFacts': [{'factValue': '2006', 'factLabel': 'Year built'}, {'factValue': '2006', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Detached Garage', 'factLabel': 'Parking'}, {'factValue': '8,220 sqft', 'factLabel': 'lotsize'}, {'factValue': '$371/sqft', 'factLabel': 'Price/sqft'}]}yesDallas[{'rating': ['9/10', '9/10', '10/10', '9/10'], 'data': {'Distance': ['1.05mi', '0.1mi', '1.05mi', '0.81mi'], 'Grades': ['5-6', 'PK-4', '7-8', '9-12']}, 'name': ['Mcculloch Intermediate School', 'Bradfield Elementary School', 'Highland Park Middle School', 'Highland Park High School']}]6,457 sqft752055 BedsTX3.0NaNNaN14191809$2,395,000
4for saleNaNlot/land1524 Kiscoe StNaN{'atAGlanceFacts': [{'factValue': '', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '10,019 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}NaNPalm Bay[{'rating': ['4/10', '5/10', '5/10'], 'data': {'Distance': ['5.96mi', '3.25mi', '3.03mi'], 'Grades': ['7-8', '9-12', 'PK-6']}, 'name': ['Southwest Middle School', 'Bayside High School', 'Westside Elementary School']}]NaN32908NaNFLNaNNaNNaN861745$5,000
5for saleNaNtownhouse1624 S Newkirk StNaN{'atAGlanceFacts': [{'factValue': '1920', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '680 sqft', 'factLabel': 'lotsize'}, {'factValue': '$233/sqft', 'factLabel': 'Price/sqft'}]}NaNPhiladelphia[{'rating': [], 'data': {'Distance': [], 'Grades': []}, 'name': []}]897 sqft191452 BedsPA2.0NaNNaNPAPH847006$209,000
6ActiveNaNFlorida552 Casanova CtNaN{'atAGlanceFacts': [{'factValue': '2006', 'factLabel': 'Year built'}, {'factValue': '2006', 'factLabel': 'Remodeled year'}, {'factValue': 'Electric, Heat Pump', 'factLabel': 'Heating'}, {'factValue': 'Central Air', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '4,996 Sq. Ft.', 'factLabel': 'lotsize'}, {'factValue': '$120 / Sq. Ft.', 'factLabel': 'Price/sqft'}]}NaNPOINCIANA[{'rating': ['3', '3', '1', 'NR'], 'data': {'Distance': ['0.8 mi', '8.3 mi', '4.2 mi', '2.0 mi'], 'Grades': ['Preschool to 4', 'Preschool to 12', '5 to 8', '1 to 12']}, 'name': ['Palmetto Elementary School', 'Haines City Senior High School', 'Lake Marion Creek Elementary School', 'Chosen Generation Christian Academy']}]1,50734759NaNFLOneNaNNaNS5026943181,500
7ActiveNaNNaN6094 Mingle DrNaN{'atAGlanceFacts': [{'factValue': '1976', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '8,750 Sq. Ft.', 'factLabel': 'lotsize'}, {'factValue': '$57 / Sq. Ft.', 'factLabel': 'Price/sqft'}]}NaNMemphis[{'rating': ['4', '2', '2'], 'data': {'Distance': ['0.7 mi', '0.4 mi', '2.2 mi'], 'Grades': ['Preschool to 5', '6 to 8', '9 to 12']}, 'name': ['Crump Elementary School', 'Hickory Ridge Middle School', 'Wooddale High School']}]NaN38115NaNTNNaNNaNNaN1006350668,000
8ActiveNaNSingle Family Home11182 Owl Ave2{'atAGlanceFacts': [{'factValue': '1970', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '124582', 'factLabel': 'lotsize'}, {'factValue': '$68', 'factLabel': 'Price/sqft'}]}NaNMason City[{'rating': ['2', '2', '4', '7', '4', 'NR'], 'data': {'Distance': ['5.6 mi', '5.6 mi', '6.8 mi', '6.5 mi', '6.8 mi', '6.8 mi'], 'Grades': ['PK–4', '5–6', '9–12', 'PK–4', '7–8', '9–12']}, 'name': ['Roosevelt Elementary School', 'Lincoln Intermediate School', 'Mason City High School', 'Jefferson Elementary School', 'John Adams Middle School', 'Alternative School']}]3588504013IANaNNaNNaN190988$244,900
9NaNNaNSingle Family8612 Cedar Plains Ln3{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Gas', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '2,056 sqft', 'factLabel': 'lotsize'}, {'factValue': '$162', 'factLabel': 'Price/sqft'}]}NaNHouston[{'rating': ['4/10', '3/10', '2/10'], 'data': {'Distance': ['0.7 mi', '0.6 mi', '1.9 mi'], 'Grades': ['PK-5', '5-8', '9-12']}, 'name': ['Edgewood Elementary School', 'Landrum Middle School', 'Northbrook High School']}]1,930770803TX2.0NaNNaN73968331$311,995
statusprivate poolpropertyTypestreetbathshomeFactsfireplacecityschoolssqftzipcodebedsstatestoriesmls-idPrivatePoolMlsIdtarget
377175for saleNaNsingle-family home9711 Lawngate Dr3 Baths{'atAGlanceFacts': [{'factValue': '1970', 'factLabel': 'Year built'}, {'factValue': '1970', 'factLabel': 'Remodeled year'}, {'factValue': 'Other', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Detached Garage', 'factLabel': 'Parking'}, {'factValue': '6,599 sqft', 'factLabel': 'lotsize'}, {'factValue': '$156/sqft', 'factLabel': 'Price/sqft'}]}yesHouston[{'rating': ['2/10', '3/10', '3/10'], 'data': {'Distance': ['0.65mi', '1.15mi', '0.19mi'], 'Grades': ['9-12', 'PK-5', '6-8']}, 'name': ['Northbrook High School', 'Terrace Elementary School', 'Northbrook Middle School']}]1,792 sqft770804 BedsTX2.0NaNNaN74136719$280,000
377176NaNNaNSingle Family3263 Wolcott Pl2.0{'atAGlanceFacts': [{'factValue': '1962', 'factLabel': 'Year built'}, {'factValue': '1967', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '1 space', 'factLabel': 'Parking'}, {'factValue': '7,704 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}YesOrlando[{'rating': ['3/10', '1/10', '3/10'], 'data': {'Distance': ['1.5 mi', '1.3 mi', '1.1 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Washington Shores Elementary School', 'Carver Middle School', 'Jones High School']}]1,829 sqft328053FL1NaNNaNNaN$171,306
377177ActiveNaNSingle Detached, Traditional2805 S Jennings AveNaN{'atAGlanceFacts': [{'factValue': '1921', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': 'Central A/C (Electric), Central Heat (Electric)', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '7,500 Sq. Ft.', 'factLabel': 'lotsize'}, {'factValue': '$105 / Sq. Ft.', 'factLabel': 'Price/sqft'}]}NaNFort Worth[{'rating': ['4', '6', '5'], 'data': {'Distance': ['0.5 mi', '2.0 mi', '1.3 mi'], 'Grades': ['Preschool to 5', '6 to 8', '9 to 12']}, 'name': ['Daggett Elementary School', 'Rosemont Middle School', 'Paschal High School']}]1,89576110NaNTXNaNNaNNaN14087883199,900
377178NaNNaNSingle FamilyBuildable plan: The Torino (384L) Riverstone Ranch - Premier2{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'No Data', 'factLabel': 'Heating'}, {'factValue': 'No Data', 'factLabel': 'Cooling'}, {'factValue': '2 spaces', 'factLabel': 'Parking'}, {'factValue': 'No Data', 'factLabel': 'lotsize'}, {'factValue': '$137', 'factLabel': 'Price/sqft'}]}NaNHouston[{'rating': ['7/10', '6/10', '5/10'], 'data': {'Distance': ['0.3 mi', '2.5 mi', '2.5 mi'], 'Grades': ['PK-4', '7-8', '9-12']}, 'name': ['South Belt Elementary School', 'Thompson Intermediate School', 'Dobie High School']}]1,841770894TX1.0NaNNaNNaN$252,990
377179For saleNaNCondo2238 11th St NW APT 23{'atAGlanceFacts': [{'factValue': '2010', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Forced air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '1 space', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$564', 'factLabel': 'Price/sqft'}]}NaNWashington[{'rating': ['3/10', '3/10'], 'data': {'Distance': ['0.4 mi', '0.1 mi'], 'Grades': ['PK-5', '6-12']}, 'name': ['Garrison Elementary School', 'Cardozo Education Campus']}]1,417200012DC3.0NaNNaNDCDC444306$799,000
377180NaNNaNSingle Family20800 NE 23rd Ave6.0{'atAGlanceFacts': [{'factValue': '1990', 'factLabel': 'Year built'}, {'factValue': '1990', 'factLabel': 'Remodeled year'}, {'factValue': 'Other', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '2 spaces', 'factLabel': 'Parking'}, {'factValue': '8,500 sqft', 'factLabel': 'lotsize'}, {'factValue': '$311', 'factLabel': 'Price/sqft'}]}NaNMiami[{'rating': ['10/10', '5/10'], 'data': {'Distance': ['32.1 mi', '1.1 mi'], 'Grades': ['PK-8', '9-12']}, 'name': ['Air Base Elementary School', 'Dr Michael M. Krop Senior High School']}]4,017331805FL0.0NaNYesA10702700$1,249,000
377181for saleNaNcondo3530 N Lake Shore Dr #4B3 Baths{'atAGlanceFacts': [{'factValue': '1924', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Radiant', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': 'None', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$337/sqft', 'factLabel': 'Price/sqft'}]}NaNChicago[{'rating': ['1/10', '5/10', '7/10'], 'data': {'Distance': ['10.61mi', '1.42mi', '0.4mi'], 'Grades': ['9-12', '9-12', 'PK-8']}, 'name': ['Hope College Prep High School', 'Lake View High School', 'Nettelhorst Elementary School']}]2,000 sqft606573 BedsIL9.0NaNNaN10374233$674,999
377182for saleNaNsingle-family home15509 Linden Blvd3 Baths{'atAGlanceFacts': [{'factValue': '1950', 'factLabel': 'Year built'}, {'factValue': '1950', 'factLabel': 'Remodeled year'}, {'factValue': 'Other', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '2', 'factLabel': 'Parking'}, {'factValue': '1,600 sqft', 'factLabel': 'lotsize'}, {'factValue': '$458/sqft', 'factLabel': 'Price/sqft'}]}NaNJamaica[{'rating': ['5/10', '4/10'], 'data': {'Distance': ['0.48mi', '0.73mi'], 'Grades': ['PK-5', '6-8']}, 'name': ['Ps 48 William Wordsworth', 'Jhs 8 Richard S Grossley']}]1,152 sqft114343 BedsNY2NaNNaNNaN$528,000
377183NaNNaNNaN7810 Pereida StNaN{'atAGlanceFacts': [{'factValue': None, 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': None, 'factLabel': 'Heating'}, {'factValue': None, 'factLabel': 'Cooling'}, {'factValue': None, 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}NaNHouston[{'rating': ['NA', 'NA', 'NA'], 'data': {'Distance': ['1.3 mi', '0.5 mi', '1.9 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Hiliard El', 'Forest Brook Middle', 'North Forest High School']}]NaN770288,479 sqftTXNaNNaNNaNNaN$34,500
377184NaNNaNSingle Family5983 Midcrown Dr2.0{'atAGlanceFacts': [{'factValue': '2019', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Electric', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'No Data', 'factLabel': 'Parking'}, {'factValue': '6,969 sqft', 'factLabel': 'lotsize'}, {'factValue': '$140', 'factLabel': 'Price/sqft'}]}Not ApplicableSan Antonio[{'rating': ['5/10', '4/10', '3/10'], 'data': {'Distance': ['0.3 mi', '1.1 mi', '4.1 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Mary Lou Hartman', 'Woodlake Hills Middle School', 'Judson High School']}]1,462782183TX1.0NaNNaN1403619$204,900

Duplicate rows

Most frequently occurring

statusprivate poolpropertyTypestreetbathshomeFactsfireplacecityschoolssqftzipcodebedsstatestoriesmls-idPrivatePoolMlsIdtarget# duplicates
46for saleNaNtownhouseThe Lockland 27-33 Plan in Landen Pine3.5 Baths{'atAGlanceFacts': [{'factValue': '', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$299/sqft', 'factLabel': 'Price/sqft'}]}NaNAtlanta[{'rating': ['6/10', '6/10', '6/10'], 'data': {'Distance': ['3.85mi', '0.65mi', '1.88mi'], 'Grades': ['10-12', 'PK-5', '6-8']}, 'name': ['North Atlanta High School', 'Smith Elementary School', 'Sutton Middle School']}]2,806 sqft303054 BedsGANaNNaNNaNNaN$839,900+3
0For saleNaNSingle Family11207 NE 127th Ave2.0{'atAGlanceFacts': [{'factValue': '2015', 'factLabel': 'Year built'}, {'factValue': '2015', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '2 spaces', 'factLabel': 'Parking'}, {'factValue': '5,662 sqft', 'factLabel': 'lotsize'}, {'factValue': '$246', 'factLabel': 'Price/sqft'}]}NaNVancouver[{'rating': ['4/10', '4/10', '6/10'], 'data': {'Distance': ['2.1 mi', '2.1 mi', '0.8 mi'], 'Grades': ['PK-4', '5-8', '9-12']}, 'name': ['Glenwood Heights Primary School', 'Laurin Middle School', 'Prairie High School']}]1,670986823WA1NaNNaN19047778$410,0002
1New constructionNaNMulti Family335 H St NENaN{'atAGlanceFacts': [{'factValue': '2017', 'factLabel': 'Year built'}, {'factValue': None, 'factLabel': 'Remodeled year'}, {'factValue': 'Forced air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'No Data', 'factLabel': 'Parking'}, {'factValue': None, 'factLabel': 'lotsize'}, {'factValue': '$651', 'factLabel': 'Price/sqft'}]}NaNWashington[{'rating': ['8/10', '6/10', '4/10'], 'data': {'Distance': ['0.2 mi', '0.2 mi', '1.5 mi'], 'Grades': ['PK-5', '6-8', '9-12']}, 'name': ['Ludlow-Taylor Elementary School', 'Stuart-Hobson Middle School', 'Eastern High School']}]3,600 sqft200020DC4NaNNaN1000123741$2,345,0002
2for saleNaNapartment269 W 87th St #B6 Baths{'atAGlanceFacts': [{'factValue': '2018', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$2,447/sqft', 'factLabel': 'Price/sqft'}]}NaNNew York[{'rating': ['8/10'], 'data': {'Distance': ['0.23mi'], 'Grades': ['K-5']}, 'name': ['Ps 166 The Richard Rogers School Of The Arts And S']}]3,882 sqft100245 BedsNYNaNNaNNaN1245762$9,500,0002
3for saleNaNcondo1517 Briarcliff Rd NE #C3 Baths{'atAGlanceFacts': [{'factValue': '2018', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$368/sqft', 'factLabel': 'Price/sqft'}]}NaNAtlanta[{'rating': ['5/10', '5/10', '6/10'], 'data': {'Distance': ['1.02mi', '1.11mi', '3.91mi'], 'Grades': ['PK-5', '9-12', '6-8']}, 'name': ['Briar Vista Elementary School', 'Druid Hills High School', 'Druid Hills Middle School']}]2,386 sqft303062 BedsGANaNNaNNaN6126572$877,8602
4for saleNaNcondo184 Kent Ave #A314NaN{'atAGlanceFacts': [{'factValue': '1915', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$1,369/sqft', 'factLabel': 'Price/sqft'}]}NaNBrooklyn[{'rating': ['6/10'], 'data': {'Distance': ['0.5mi'], 'Grades': ['PK-5']}, 'name': ['Ps 17 Henry D Woodworth']}]712 sqft11249NaNNYNaNNaNNaN1123517$975,0002
5for saleNaNcondo184 Kent Ave #B3012 Baths{'atAGlanceFacts': [{'factValue': '1915', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': '$1,855/sqft', 'factLabel': 'Price/sqft'}]}NaNBrooklyn[{'rating': ['6/10'], 'data': {'Distance': ['0.47mi'], 'Grades': ['PK-5']}, 'name': ['Ps 17 Henry D Woodworth']}]1,078 sqft112492 BedsNYNaNNaNNaN1062169$2,000,0002
6for saleNaNcondo519 Circle St #A4 Baths{'atAGlanceFacts': [{'factValue': '2007', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': 'Forced Air', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': 'Attached Garage', 'factLabel': 'Parking'}, {'factValue': '9,714 sqft', 'factLabel': 'lotsize'}, {'factValue': '$192/sqft', 'factLabel': 'Price/sqft'}]}yesAlamo Heights[{'rating': ['7/10', '7/10', '6/10'], 'data': {'Distance': ['0.75mi', '1.45mi', '0.12mi'], 'Grades': ['9-12', '6-8', '1-5']}, 'name': ['Alamo Heights High School', 'Alamo Heights J High School', 'Cambridge Elementary School']}]3,385 sqft782094 BedsTXNaNNaNNaN1363375$650,0002
7for saleNaNcoop152 W 58th St #12 Baths{'atAGlanceFacts': [{'factValue': '1916', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': 'Central', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}yesNew York[{'rating': ['9/10', '8/10', '3/10', '8/10', '9/10', '5/10'], 'data': {'Distance': ['2.02mi', '2.02mi', '2.1mi', '2.16mi', '4.52mi', '0.58mi'], 'Grades': ['6-8', '9-12', '6-12', '6-11', '6-8', 'PK-5']}, 'name': ['Nyc Lab Ms For Collaborative Studies', 'Nyc Lab High School For Collaborative Studies', 'Life Sciences Secondary School', 'Ms 260 Clinton School Writers And Artists', 'Lower Manhattan Community Middle School', 'Ps 111 Adolph S Ochs']}]NaN100193 BedsNYNaNNaNNaN1230018$2,500,0002
8for saleNaNlot/land116 Country Club RdNaN{'atAGlanceFacts': [{'factValue': '', 'factLabel': 'Year built'}, {'factValue': '', 'factLabel': 'Remodeled year'}, {'factValue': '', 'factLabel': 'Heating'}, {'factValue': '', 'factLabel': 'Cooling'}, {'factValue': '', 'factLabel': 'Parking'}, {'factValue': '7840 sqft', 'factLabel': 'lotsize'}, {'factValue': None, 'factLabel': 'Price/sqft'}]}NaNAsheville[{'rating': ['8/10', '5/10', '5/10', '7/10', '4/10', '6/10', '4/10', '6/10'], 'data': {'Distance': ['3.34mi', '1.98mi', '3.34mi', '3.51mi', '0.95mi', '0.63mi', '2.46mi', '4.23mi'], 'Grades': ['9-12', 'PK-5', '9-12', 'PK-5', 'K-5', 'PK-5', '6-8', 'K-5']}, 'name': ['School Of Inquiry And Life Science', 'Isaac Dickson Elementary', 'Asheville High', 'Hall Fletcher Elementary', 'Claxton Elementary', 'Ira B Jones Elementary', 'Asheville Middle', 'Vance Elementary']}]NaN28804NaNNCNaNNaNNaN3462298$169,9002